The use of probabilistic evolutionary models is an integral part of comparative genomics. Applications include design of evolutionary genefinding software; screening of coding DNA sequences for sites under selection; identification of regulatory elements in genomes; improved detection of homologues;and prediction of deleterious SNPs. Such evolutionary models remain under-developed, particularly for the subclass of genes expressed solely as noncoding RNA (ncRNA). However, there is increasing biomedical interest in this class of genes: microRNAs are now suspected to regulate a wide range of targets, and are used by viruses to silence host transcription; small interfering RNAs are being explored as atherapeutic treatment; drugs exist that specifically target RNA structure (e.g. bacterial ribosomes, or retroviral binding sites such as HIV's Rev Response Element); RNA motifs known as """"""""riboswitches"""""""", echoing genetically- engineered """"""""aptamers"""""""" in their ability to discriminatively bind small-molecule ligands, have recently been discovered in prokaryotes; many catalytic ncRNAs (""""""""ribozymes"""""""") are active in human and bacterial cells; and many of the above technologies (e.g. riboswitches/ aptamers/ ribozymes) are beginning to be exploited by synthetic biologists e.g. as novel reporter constructs, with great biomedical potential. Here, we propose to develop ncRNA evolutionary models for a focussed, biologically testable case study: the identification of ncRNA genes by comparative analysis of twelve fruitfly genomes. Computationally, we will use this example to drive forward our ongoing methods development in RNA analysis and evolutionary modeling, adapting our successful """"""""xrate"""""""" and """"""""stemloc"""""""" programs for use with evolutionarystochastic context-free grammars. Experimentally, we will test our predictions by wet-lab validation methods such as RT-PCR and sequencing, with the help of our collaboratorsand locally available resources such as the Berkeley Drosophila Genome Project's cDNA libraries. All our software will be freely available online.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Genetic Variation and Evolution Study Section (GVE)
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Eckstrand, Irene A
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University of California Berkeley
Biomedical Engineering
Schools of Engineering
United States
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Westesson, Oscar; Lunter, Gerton; Paten, Benedict et al. (2012) Accurate reconstruction of insertion-deletion histories by statistical phylogenetics. PLoS One 7:e34572
Westesson, Oscar; Barquist, Lars; Holmes, Ian (2012) HandAlign: Bayesian multiple sequence alignment, phylogeny and ancestral reconstruction. Bioinformatics 28:1170-1
Mork, Soren; Holmes, Ian (2012) Evaluating bacterial gene-finding HMM structures as probabilistic logic programs. Bioinformatics 28:636-42
Holmes, Ian; Harris, Keith; Quince, Christopher (2012) Dirichlet multinomial mixtures: generative models for microbial metagenomics. PLoS One 7:e30126
Bradley, Robert K; Uzilov, Andrew V; Skinner, Mitchell E et al. (2009) Evolutionary modeling and prediction of non-coding RNAs in Drosophila. PLoS One 4:e6478
Bradley, Robert K; Holmes, Ian (2009) Evolutionary triplet models of structured RNA. PLoS Comput Biol 5:e1000483
Bradley, Robert K; Roberts, Adam; Smoot, Michael et al. (2009) Fast statistical alignment. PLoS Comput Biol 5:e1000392
Westesson, Oscar; Holmes, Ian (2009) Accurate detection of recombinant breakpoints in whole-genome alignments. PLoS Comput Biol 5:e1000318
Varadarajan, Avinash; Bradley, Robert K; Holmes, Ian H (2008) Tools for simulating evolution of aligned genomic regions with integrated parameter estimation. Genome Biol 9:R147
Bradley, Robert K; Pachter, Lior; Holmes, Ian (2008) Specific alignment of structured RNA: stochastic grammars and sequence annealing. Bioinformatics 24:2677-83

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